The impact of black carbon (BC) on mode-specific galvanic skin response (GSR) as a measure of stress in urban environments.

Previous research has shown that walking and cycling could help alleviate stress in cities, however there is poor knowledge on how specific microenvironmental conditions encountered during daily journeys may lead to varying degrees of stress experienced at that moment. We use objectively measured data and a robust causal inference framework to address this gap. Using a Bayesian Doubly Robust (BDR) approach, we find that black carbon exposure statistically significantly increases stress, as measured by Galvanic Skin Response (GSR), while cycling and while walking. Augmented Outcome Regression (AOR) models indicate that greenspace exposure and the presence of walking or cycling infrastructure could reduce stress. None of these effects are statistically significant for people in motorized transport. These findings add to a growing evidence-base on health benefits of policies aimed at decreasing air pollution, improving active travel infrastructure and increasing greenspace in cities.

Effects of physical activity and air pollution on blood pressure.

AIM: To assess the main and interaction effects of black carbon and physical activity on arterial blood pressure in a healthy adult population from three European cities using objective personal measurements over short-term (hours and days) and long-term exposure. METHODS: A panel study of 122 healthy adults was performed in three European cities (Antwerp, Barcelona, and London). In 3 seasons between March 2015 and March 2016, each participant wore sensors for one week to objectively measure their exposure to black carbon and monitor their physical activity continuously. Blood pressure was assessed three times during the week: at the beginning (day 0), in the middle (day 4), and at the end (day 7). Associations of black carbon and physical activity with blood pressure and their interactions were investigated with linear regression models and multiplicative interaction terms, adjusting for all the potential confounders. RESULTS: In multiple exposure models, we did not see any effects of black carbon on blood pressure but did see effects on systolic blood pressure of moderate-to-vigorous physical activity effect that were statistically significant from 1 h to 8 h after exposure and for long-term exposure. For a 1METhour increase of moderate-to-vigorous physical activity, the difference in the expected mean systolic blood pressure varied from -1.46 mmHg (95%CI -2.11, -0.80) for 1 h mean exposure, to -0.29 mmHg (95%CI -0.55, -0.03) for 8 h mean exposure, and -0.05 mmHg (95%CI -0.09, -0.00) for long-term exposure. There were little to no interaction effects. CONCLUSIONS: Results from this study provide evidence that short-term and long-term exposure to moderate-to-vigorous physical activity is associated with a decrease in systolic blood pressure levels. We did not find evidence for a consistent main effect of black carbon on blood pressure, nor any interaction between black carbon and physical activity levels.

The effects of transport mode use on self-perceived health, mental health, and social contact measures: A cross-sectional and longitudinal study.

BACKGROUND: Transport mode choice has been associated with different health risks and benefits depending on which transport mode is used. We aimed to evaluate the association between different transport modes use and several health and social contact measures. METHODS: We based our analyses on the Physical Activity through Sustainable Transport Approaches (PASTA) longitudinal study, conducted over a period of two years in seven European cities. 8802 participants finished the baseline questionnaire, and 3567 answered the final questionnaire. Participants were 18 years of age or older (16 years of age or older in Zurich) and lived, worked and/or studied in one of the case-study cities. Associations between transport mode use and health/social contact measures were estimated using mixed-effects logistic regression models, linear regression models, and logistic regression models according to the data available. All the associations were assessed with single and multiple transport mode models. All models were adjusted for potential confounders. RESULTS: In multiple transport mode models, bicycle use was associated with good self-perceived health [OR (CI 95%) = 1.07 (1.05, 1.08)], all the mental health measures [perceived stress: coef (CI 95%) = -0.016 (-0.028, -0.004); mental health: coef (CI 95%) = 0.11 (0.05, 0.18); vitality: coef (CI 95%) = 0.14 (0.07, 0.22)], and with fewer feelings of loneliness [coef (CI 95%) = -0.03 (-0.05, -0.01)]. Walking was associated with good self-perceived health [OR (CI 95%) = 1.02 (1.00, 1.03)], higher vitality [coef (CI 95%) = 0.14 (0.05, 0.23)], and more frequent contact with friends/family [OR (CI 95%) = 1.03 (1.00, 1.05)]. Car use was associated with fewer feelings of loneliness [coef (CI 95%) = -0.04 (-0.06, -0.02)]. The results for e-bike and public transport use were non-significant, and the results for motorbike use were inconclusive. CONCLUSIONS: Similarity of findings across cities suggested that active transport, especially bicycle use, should be encouraged to improve population health and social outcomes.

Transport mode choice and body mass index: Cross-sectional and longitudinal evidence from a European-wide study.

BACKGROUND: In the fight against rising overweight and obesity levels, and unhealthy urban environments, the renaissance of active mobility (cycling and walking as a transport mode) is encouraging. Transport mode has been shown to be associated to body mass index (BMI), yet there is limited longitudinal evidence demonstrating causality. We aimed to associate transport mode and BMI cross-sectionally, but also prospectively in the first ever European-wide longitudinal study on transport and health. METHODS: Data were from the PASTA project that recruited adults in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich) to complete a series of questionnaires on travel behavior, physical activity levels, and BMI. To assess the association between transport mode and BMI as well as change in BMI we performed crude and adjusted linear mixed-effects modeling for cross-sectional (n = 7380) and longitudinal (n = 2316) data, respectively. RESULTS: Cross-sectionally, BMI was 0.027 kg/m2 (95%CI 0.015 to 0.040) higher per additional day of car use per month. Inversely, BMI was -0.010 kg/m2 (95%CI -0.020 to -0.0002) lower per additional day of cycling per month. Changes in BMI were smaller in the longitudinal within-person assessment, however still statistically significant. BMI decreased in occasional (less than once per week) and non-cyclists who increased cycling (-0.303 kg/m2, 95%CI -0.530 to -0.077), while frequent (at least once per week) cyclists who stopped cycling increased their BMI (0.417 kg/m2, 95%CI 0.033 to 0.802). CONCLUSIONS: Our analyses showed that people lower their BMI when starting or increasing cycling, demonstrating the health benefits of active mobility.

Short-term effects of physical activity, air pollution and their interaction on the cardiovascular and respiratory system.

Physical activity (PA) in urban environments may lead to increased inhalation of air pollutants. As PA and air pollution (AP) have respectively beneficial and detrimental effects on the cardiorespiratory system, the responses to these exposures can interact. Therefore, we assessed the short-term effects of PA, AP and their interaction on a set of subclinical cardiovascular and respiratory outcomes in a panel of healthy adults: heart rate variability (HRV), retinal vessel diameters, lung function and fractional exhaled nitric oxide (FeNO). One hundred twenty two participants measured their PA level and exposure to black carbon (BC), a marker of AP exposure, with wearable sensors during an unscripted week in three different seasons. The study was part of the PASTA project in three European cities (Antwerp: 41 participants, Barcelona: 41 participants, London: 40 participants). At the end of each measurement week, the health outcomes were evaluated. Responses to PA, BC and their interaction were assessed with mixed effect regression models. Separate models were used to account for a 2-h and 24-h time window. During the 2-h time window, HRV and lung function changed statistically significantly in response to PA (METhours) and logarithmic BC (%change). Changes in HRV marked an increased sympathetic tone with both PA (logarithmic LF/HF: +7%; p < 0.01) and BC (logarithmic HF: -19%; p < 0.05). In addition, PA provoked bronchodilation which was illustrated by a significant increase in lung function (FEV1: +15.63 mL; p < 0.05). While a BC %increase was associated with a significant lung function decrease (PEF: -0.10 mL; p < 0.05), the interaction indicated a potential protective effect of PA (p < 0.05). We did not observe a response of the retinal vessel diameters. Most subclinical outcomes did not change in the 24-h time window (except for a few minor changes in LF/HF, FeNO and PEF). Our results on the separate and combined effects of short-term PA and AP exposure on subclinical markers of the cardiorespiratory system are relevant for public health. We provide insights on the physiological responses of multiple, complementary markers. This may move further research towards elucidating potential pathways to disease and the long-term clinical impact of the observed physiological changes.

Physical activity and sedentary behaviour in daily life: A comparative analysis of the Global Physical Activity Questionnaire (GPAQ) and the SenseWear armband.

Reduction of sedentary time and an increase in physical activity offer potential to improve public health. However, quantifying physical activity behaviour under real world conditions is a major challenge and no standard of good practice is available. Our aim was to compare the results of physical activity and sedentary behaviour obtained with a self-reported instrument (Global Physical Activity Questionnaire (GPAQ)) and a wearable sensor (SenseWear) in a repeated measures study design. Healthy adults (41 in Antwerp, 41 in Barcelona and 40 in London) wore the SenseWear armband for seven consecutive days and completed the GPAQ on the final day. This was repeated three times. We used the Wilcoxon signed rank sum test, Spearman correlation coefficients, mixed effects regression models and Bland-Altman plots to study agreement between both methods. Mixed models were used to assess the effect of personal characteristics on the absolute and relative difference between estimates obtained with the GPAQ and SenseWear. Moderate to vigorous energy expenditure and duration derived from the GPAQ were significantly lower (p<0.05) compared to the SenseWear, yet these variables showed significant correlations ranging from 0.45 to 0.64. Estimates of vigorous-intensity physical activity in particular showed high similarity (r>0.59). Results for sedentary behaviour did not differ, yet were poorly correlated (r<0.25). The differences between all variables were reproducible across repeated measurements. In addition, we observed a relationship between these differences and BMI, body fat and physical activity domain. Due to the lack of a standardized protocol, results from different studies measuring physical activity and sedentary behaviour are difficult to compare. Therefore, we suggested an easy-to-implement approach for future studies adding the GPAQ to the wearable of choice as a basis for comparisons.

Wearable Sensors for Personal Monitoring and Estimation of Inhaled Traffic-Related Air Pollution: Evaluation of Methods.

Physical activity and ventilation rates have an effect on an individual's dose and may be important to consider in exposure-response relationships; however, these factors are often ignored in environmental epidemiology studies. The aim of this study was to evaluate methods of estimating the inhaled dose of air pollution and understand variability in the absence of a true gold standard metric. Five types of methods were identified: (1) methods using (physical) activity types, (2) methods based on energy expenditure, METs (metabolic equivalents of task), and oxygen consumption, (3) methods based on heart rate or (4) breathing rate, and (5) methods that combine heart and breathing rate. Methods were compared using a real-life data set of 122 adults who wore devices to track movement, black carbon air pollution, and physiological health markers for 3 weeks in three European cities. Different methods for estimating minute ventilation performed well in relative terms with high correlations among different methods, but in absolute terms, ignoring increased ventilation during day-to-day activities could lead to an underestimation of the daily dose by a factor of 0.08-1.78. There is no single best method, and a multitude of methods are currently being used to approximate the dose. The choice of a suitable method for determining the dose in future studies will depend on both the size and the objectives of the study.

Comparison of air pollution exposures in active vs. passive travel modes in European cities: A quantitative review.

BACKGROUND: Transport microenvironments tend to have higher air pollutant concentrations than other settings most people encounter in their daily lives. The choice of travel modes may affect significantly individuals' exposures; however such considerations are typically not accounted for in exposure assessment used in environmental health studies. In particular, with increasing interest in the promotion of active travel, health impact studies that attempt to estimate potential adverse consequences of potential increased pollutant inhalation during walking or cycling have emerged. Such studies require a quantification of relative exposures in travel modes. METHODS: The literature on air pollution exposures in travel microenvironments in Europe was reviewed. Studies which measured various travel modes including at least walking or cycling in a simultaneous or quasi-simultaneous design were selected. Data from these studies were harmonized to allow for a quantitative synthesis of the estimates. Ranges of ratios and 95% confidence interval (CI) of air pollution exposure between modes and between background and transportation modes were estimated. RESULTS: Ten studies measuring fine particulate matter (PM2.5), black carbon (BC), ultrafine particles (UFP), and/or carbon monoxide (CO) in the walk, bicycle, car and/or bus modes were included in the analysis. Only three reported on CO and BC and results should be interpreted with caution. Pedestrians were shown to be the most consistently least exposed of all across studies, with the bus, bicycle and car modes on average 1.3 to 1.5 times higher for PM2.5; 1.1 to 1.7 times higher for UFP; and 1.3 to 2.9 times higher for CO; however the 95% CI included 1 for the UFP walk to bus ratio. Only for BC were pedestrians more exposed than bus users on average (bus to walk ratio 0.8), but remained less exposed than those on bicycles or in cars. Car users tended to be the most exposed (from 2.9 times higher than pedestrians for BC down to similar exposures to cyclists for UFP on average). Bus exposures tended to be similar to that of cyclists (95% CI including 1 for PM2.5, CO and BC), except for UFP where they were lower (ratio 0.7). CONCLUSION: A quantitative method that synthesizes the literature on air pollution exposure in travel microenvironments for use in health impact assessments or potentially for epidemiology was conducted. Results relevant for the European context are presented, showing generally greatest exposures in car riders and lowest exposure in pedestrians.

Physical Activity through Sustainable Transport Approaches (PASTA): a study protocol for a multicentre project.

INTRODUCTION: Only one-third of the European population meets the minimum recommended levels of physical activity (PA). Physical inactivity is a major risk factor for non-communicable diseases. Walking and cycling for transport (active mobility, AM) are well suited to provide regular PA. The European research project Physical Activity through Sustainable Transport Approaches (PASTA) pursues the following aims: (1) to investigate correlates and interrelations of AM, PA, air pollution and crash risk; (2) to evaluate the effectiveness of selected interventions to promote AM; (3) to improve health impact assessment (HIA) of AM; (4) to foster the exchange between the disciplines of public health and transport planning, and between research and practice. METHODS AND ANALYSIS: PASTA pursues a mixed-method and multilevel approach that is consistently applied in seven case study cities. Determinants of AM and the evaluation of measures to increase AM are investigated through a large scale longitudinal survey, with overall 14,000 respondents participating in Antwerp, Barcelona, London, Örebro, Rome, Vienna and Zurich. Contextual factors are systematically gathered in each city. PASTA generates empirical findings to improve HIA for AM, for example, with estimates of crash risks, factors on AM-PA substitution and carbon emissions savings from mode shifts. Findings from PASTA will inform WHO's online Health Economic Assessment Tool on the health benefits from cycling and/or walking. The study's wide scope, the combination of qualitative and quantitative methods and health and transport methods, the innovative survey design, the general and city-specific analyses, and the transdisciplinary composition of the consortium and the wider network of partners promise highly relevant insights for research and practice. ETHICS AND DISSEMINATION: Ethics approval has been obtained by the local ethics committees in the countries where the work is being conducted, and sent to the European Commission before the start of the survey. The PASTA website (http://www.pastaproject.eu) is at the core of all communication and dissemination activities.

Physical Activity through Sustainable Transport Approaches (PASTA): protocol for a multi-centre, longitudinal study.

BACKGROUND: Physical inactivity is one of the leading risk factors for non-communicable diseases, yet many are not sufficiently active. The Physical Activity through Sustainable Transport Approaches (PASTA) study aims to better understand active mobility (walking and cycling for transport solely or in combination with public transport) as an innovative approach to integrate physical activity into individuals' everyday lives. The PASTA study will collect data of multiple cities in a longitudinal cohort design to study correlates of active mobility, its effect on overall physical activity, crash risk and exposure to traffic-related air pollution. METHODS/DESIGN: A set of online questionnaires incorporating gold standard approaches from the physical activity and transport fields have been developed, piloted and are now being deployed in a longitudinal study in seven European cities (Antwerp, Barcelona, London, Oerebro, Rome, Vienna, Zurich). In total, 14000 adults are being recruited (2000 in each city). A first questionnaire collects baseline information; follow-up questionnaires sent every 13 days collect prospective data on travel behaviour, levels of physical activity and traffic safety incidents. Self-reported data will be validated with objective data in subsamples using conventional and novel methods. Accelerometers, GPS and tracking apps record routes and activity. Air pollution and physical activity are measured to study their combined effects on health biomarkers. Exposure-adjusted crash risks will be calculated for active modes, and crash location audits are performed to study the role of the built environment. Ethics committees in all seven cities have given independent approval for the study. DISCUSSION: The PASTA study collects a wealth of subjective and objective data on active mobility and physical activity. This will allow the investigation of numerous correlates of active mobility and physical activity using a data set that advances previous efforts in its richness, geographical coverage and comprehensiveness. Results will inform new health impact assessment models and support efforts to promote and facilitate active mobility in cities.